The invention relates to methods of validating coins, or similar tokens having associated monetary values.
Coin-operated machines are widely used to provide goods and services to the public. These machines include, for example, amusement machines, vending machines, gaming machines and pay phones. For coin-operated machines of this type, a coin validator is typically used to determine which denomination of coin of a given currency is deposited in the machine. The coin validator usually also seeks to detect attempted fraud by distinguishing genuine coins from different coins (ie coins of a different currency, or non-genuine coins or xe2x80x9cslugsxe2x80x9d).
Coin validators typically measure one or more characteristics of a coin deposited in the machine using one or more existing measurement techniques. These techniques may include, for example, measuring:
(i) characteristics of sound signals generated after the coin strikes a surface; or
(ii) characteristics of electrical signals generated as the coin passes through an electromagnetic field.
Once data measured in connection with the deposited coin is recorded, various differing comparison methods are used to compare the measured data with reference data derived from similar measurements made in relation to a number of genuine xe2x80x9creferencexe2x80x9d coins of a particular currency. A subsequent validation process attempts to match the measured values of a deposited coin with the reference measurements of the reference coin denominations of the currency.
Developing validation processes has been the subject of some activity. Most attempts have involved relatively sophisticated data manipulation processes. For example, there are a number of published international patent applications in the name of Mars Incorporated (WO 92/07339, WO 92/18951 and WO 94/12951) that use relatively involved data manipulation methods to improve the results of the coin validation process.
In the first of the two abovementioned references, an n-dimensional space is defined by dimensions corresponding with particular measured characteristics of the deposited coin.
In WO 92/18951, for example, a number of regular n-dimensional ellipses in n-dimensional space are representative of respective coin denominations. It is determined whether the measured characteristics of a deposited coin correspond with a point within one of the n-dimensional ellipses, hence indicating that the deposited coin is of a denomination corresponding with that particular ellipse.
In the system disclosed in WO 92/18951, the centre of each n-dimensional ellipse represents the statistical mean of the measured characteristics of the respective reference coin denominations, and the length of each major axis is indicative of the standard deviation of the characteristics corresponding with these respective dimensions. The acceptance limits of the n-dimensional ellipse (and thus its is volume) can be adjusted as required by varying the length of each axis of the ellipse. This flexibility is intended to improve the results of the validation process, in view of other coins which generate similar measured characteristics to those of the genuine reference coins.
In WO 92/18951, an arbitrary n-dimensional volume is assumed, rather than a regular n-dimensional ellipse. It is also recognised that non-genuine coins can also be attributed arbitrary n-dimensional volumes representative which attempt to replicate the measured characteristics of genuine coins. It is recognised in WO 92/18951 that, for a particular denomination, the n-dimensional volume of a genuine coin may coincide with that of a non-genuine coin.
It is stated that one approach to this problem is to tighten the tolerance values for acceptance as a genuine coin (ie shrinking the n-dimensional acceptance volume representative of that coin), though this may lead to genuine coins being incorrectly rejected. Instead, this reference proposes a process whereby the n-dimensional acceptance volume for a coin denomination is adjusted by removing the overlap with a non-genuine coin if the frequency of occurrence of measured characteristics for genuine coins in that volume is sufficiently low. To increase the simplicity of comparison of measured data with reference data for a given coin denomination (amongst other reasons), it is disclosed that the measured data is normalised by linear translation to the centre of the n-dimensional acceptance volume. In effect, the mean of the n-dimensional data values representing the measured characteristics of a coin is simply removed from each dimension. Once the data is normalised in this way a comparison operation is performed using conventional techniques
It is an object of the invention to attempt to provide a data manipulation method that can be applied to coin validation to achieve enhanced coin discrimination.
The inventive concept resides in a recognition that coin validation can be advantageously improved by transforming data values from a first geometric space to a second geometric space, in which the transformed values in the second geometric space are preferably better adapted for discrimination between different coin denominations than corresponding values in the first geometric space.
While transformation between different geometric spaces is a technique that is used in various arts, these techniques have not previously been used or proposed in connection with coin validation. Various attempts have previously been made to improve the results of coin validation processes by using relatively complicated data manipulation processes in a first geometric space. However, the present applicant has recognised that the results of coin validation can be improved by taking a quite different approach which involves transforming data in a first geometric space to an appropriate second geometric space.
Accordingly, the invention provides a method of manipulating data in relation to coin validation, the method including: transforming one or more first multivariate data values in a first geometric space to one or more respective second multivariate data values in a second geometric space, said first multivariate data values corresponding with data variables related to one or more coins; wherein at least one of the basis vectors of the dimensions of said second geometric space is different from any one of the basis vectors of the dimensions of said first geometric space.
Preferably, said second multivariate data values in said second geometric space are generally less correlated than said first multivariate data values in said first geometric space.
Preferably, said second multivariate data values in said second geometric space are generally uncorrelated.
Preferably, the basis vectors of the dimensions of said second geometric space are determined with the assistance of principal component analysis on the basis of said first multivariate data values in said first geometric space.
Preferably, the number of dimensions of said second geometric space is equal to or lower than the number of dimensions of said first geometric space. Preferably, said first geometric space has three dimensions, and said second geometric space has two dimensions.
Preferably, the method further includes: establishing one or more predetermined multivariate sets of said second multivariate data values in said second geometric space, wherein said predetermined multivariate data sets can be used to assess whether a coin is of a coin denomination respectively corresponding with one of said one or more predetermined multivariate sets.
Preferably, at least one of said one or more predetermined multivariate sets are determined from average values of a plurality of said first multivariate data values, after said transformation from said first geometric space to said second geometric space.
Preferably, the method further includes: sampling variables associated with one or more coins to derive said first multivariate data values.
Preferably, the method further includes: comparing one of said second multivariate data values in said second geometric space with one or more predetermined multivariate sets in said second geometric space.
Preferably, the method further includes assessing, on the basis of said comparison of said one or more second multivariate data values with said predetermined multivariate data sets, whether said one or more second multivariate data values correspond with one of said predetermined multivariate sets and hence a respective coin denomination.
Preferably, said comparison is performed for a plurality of said second multivariate data values in respective said second geometric spaces, and each of said second geometric spaces is different from each other.
The invention also includes a method of manipulating data in relation to coin validation, the method including:
sampling variables associated with one or more coins to derive said first multivariate data values.
transforming one or more first multivariate data values in a first geometric space to one or more respective second multivariate data values in a second geometric space, said first multivariate data values corresponding with one or more sets of data variables related to one or more coins;
establishing one or more predetermined multivariate sets of said second multivariate data values in said second geometric space, wherein each of said one or more predetermined multivariate sets can be used to determine whether any of said one or more second multivariate data values correspond with respective coin denominations;
wherein at least one of the dimensions of said second geometric space is different from any one of the dimensions of said first geometric space.
The invention further includes a method of manipulating data in relation to coin validation, the method including:
sampling variables associated with one or more coins to derive one or more said first multivariate data values in a first geometric space;
transforming said one or more first multivariate data values in a first geometric space to one or more respective second multivariate data values in a second geometric space, said first multivariate data values corresponding with data variables related to one or more coins;
comparing one of said second multivariate data values in said second geometric space with one or more predetermined multivariate sets in said second geometric space, wherein each of said one or more predetermined multivariate sets correspond with respective coin denominations;
assessing, on the basis of said comparison of said one or more second multivariate data values with said predetermined multivariate data sets, whether said one or more second multivariate data values correspond with one of said predetermined multivariate sets and hence said respective coin denominations;
wherein at least one of the basis vectors of the dimensions of said second geometric space is different from any one of the basis vectors of the dimensions of said first geometric space.